scholarly journals Design of Variable Sampling Plan for Pareto Distribution Using Neutrosophic Statistical Interval Method

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 80 ◽  
Author(s):  
Muhammad Aslam ◽  
Nasrullah Khan ◽  
Ali Hussein AL-Marshadi
Keyword(s):  
Optimization Problem ◽  
Pareto Distribution ◽  
Measurement Data ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Uncertainty In Measurement ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The sampling plans have been widely used for the inspection of a lot of the product. In practice, the measurement data may be imprecise, uncertain, unclear or fuzzy. When there is uncertainty in the observations, the sampling plans designed using classical statistics cannot be applied for the inspection of a lot of the product. The neutrosophic statistic, which is the generalization of the classical statistics, can be used when data is not precise, uncertain, unclear or fuzzy. In this paper, we will design the variable sampling plan under the Pareto distribution using the neutrosophic statistics. We used the symmetry property of the normal distribution. We assume uncertainty in measurement data and sample size required for the inspection of a lot of the product. We will determine the neutrosophic plan parameters using the neutrosophic optimization problem. Some tables are given for practical use and are discussed with the help of an example.

scholarly journals Single-stage and two-stage total failure-based group-sampling plans for the Weibull distribution under neutrosophic statistics

2021 ◽  
Author(s):  
Muhammad Aslam ◽  
G. Srinivasa Rao ◽  
Nasrullah Khan
Keyword(s):  
Weibull Distribution ◽  
Shape Parameter ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Total Failure ◽  
Life Tests ◽  
Double Group

AbstractIf the sample or population has vague, inaccurate, unidentified, deficient, indecisive, or fuzzy data, then the available sampling plans could not be suitable to use for decision-making. In this article, an improved group-sampling plan based on time truncated life tests for Weibull distribution under neutrosophic statistics (NS) has been developed. We developed improved single and double group-sampling plans based on the NS. The proposed design neutrosophic plan parameters are obtained by satisfying both producer’s and consumer’s risks simultaneously under neutrosophic optimization solution. Tables are constructed for the selected shape parameter of Weibull distribution and various combinations of neutrosophic group size. The efficiency of the proposed group-sampling plan under the neutrosophic statistical interval method is also compared with the crisp method grouped sampling plan under classical statistics.

scholarly journals A Variable Acceptance Sampling Plan under Neutrosophic Statistical Interval Method

Symmetry ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 114 ◽  
Author(s):  
Muhammad Aslam
Keyword(s):  
Operating Characteristic ◽  
Fuzzy Variable ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Interval Method ◽  
Acceptance Sampling Plan ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The acceptance sampling plan plays an important role in maintaining the high quality of a product. The variable control chart, using classical statistics, helps in making acceptance or rejection decisions about the submitted lot of the product. Furthermore, the sampling plan, using classical statistics, assumes the complete or determinate information available about a lot of product. However, in some situations, data may be ambiguous, vague, imprecise, and incomplete or indeterminate. In this case, the use of neutrosophic statistics can be applied to guide the experimenters. In this paper, we originally proposed a new variable sampling plan using the neutrosophic interval statistical method. The neutrosophic operating characteristic (NOC) is derived using the neutrosophic normal distribution. The optimization solution is also presented for the proposed plan under the neutrosophic interval method. The effectiveness of the proposed plan is compared with the plan under classical statistics. The tables are presented for practical use and a real example is given to explain the neutrosophic fuzzy variable sampling plan in the industry.

scholarly journals Inspection Strategy under Indeterminacy Based on Neutrosophic Coefficient of Variation

Symmetry ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 193 ◽  
Author(s):  
Muhammad Aslam ◽  
Mansour Sattam Aldosari
Keyword(s):  
Sample Size ◽  
Coefficient Of Variation ◽  
Operating Characteristic ◽  
Uncertain Data ◽  
Sampling Plan ◽  
Sampling Plans ◽  
Interval Method ◽  
Inspection Strategy ◽  
Classical Statistics

The existing sampling plans which use the coefficient of variation (CV) are designed under classical statistics. These available sampling plans cannot be used for sentencing if the sample or the population has indeterminate, imprecise, unknown, incomplete or uncertain data. In this paper, we introduce the neutrosophic coefficient of variation (NCV) first. We design a sampling plan based on the NCV. The neutrosophic operating characteristic (NOC) function is then given and used to determine the neutrosophic plan parameters under some constraints. The neutrosophic plan parameters such as neutrosophic sample size and neutrosophic acceptance number are determined through the neutrosophic optimization solution. We compare the efficiency of the proposed plan under the neutrosophic statistical interval method with the sampling plan under classical statistics. A real example which has indeterminate data is given to illustrate the proposed plan.

scholarly journals Product Acceptance Determination with Measurement Error Using the Neutrosophic Statistics

2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Muhammad Aslam
Keyword(s):  
Measurement Error ◽  
Sample Size ◽  
Optimization Problem ◽  
Sampling Plan ◽  
Measurement Process ◽  
Comparison Study ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Variable Data ◽  
Uncertainty Environment

The variable data is obtained from the measurement process which is not fully complete or clear in nature due to measurement error. The neutrosophic statistics which is the extension of classical statistics can be applied in the industry for the lot senescing when observations or parameters are uncertain or indeterminate or unclear. In this manuscript, a new sampling plan for the measurement error using the neutrosophic statistics is designed. The proposed sampling plan has two neutrosophic parameters, namely, sample size and acceptance number. The neutrosophic operating function is also given. The neutrosophic plan parameters will be determined through the neutrosophic optimization problem. Some tables are given for some specified parameters. From the comparison study, it is concluded that the proposed sampling plan is more flexible, adequate, and effective in the uncertainty environment as compared to the existing sampling plan under the classical statistics. A real example is given for the illustration purpose.

scholarly journals Inspection Plan Based on the Process Capability Index Using the Neutrosophic Statistical Method

Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 631 ◽  
Author(s):  
Aslam ◽  
Albassam
Keyword(s):  
Production Process ◽  
Statistical Method ◽  
Process Capability ◽  
Process Capability Index ◽  
Sampling Plan ◽  
Capability Index ◽  
Variable Sampling ◽  
Classical Statistics ◽  
Neutrosophic Statistics

The Process Capability Index (PCI) has been widely used in industry to advance the quality of a product. Neutrosophic statistics is the more generalized form of classical statistics and is applied when the data from the production process or a product lot is incomplete, incredible, and indeterminate. In this paper, we will originally propose a variable sampling plan for the PCI using neutrosophic statistics. The neutrosophic operating function will be given. The neutrosophic plan parameters will be determined using the neutrosophic optimization solution. A comparison between plans based on neutrosophic statistics and classical statistics is given. The application of the proposed neutrosophic sampling plan will be given using company data.

scholarly journals Design of Sampling Plan Using Regression Estimator under Indeterminacy

Symmetry ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 754 ◽  
Author(s):  
Muhammad Aslam ◽  
Ali AL-Marshadi
Keyword(s):  
Auxiliary Information ◽  
Sampling Plan ◽  
Acceptance Sampling ◽  
Regression Estimator ◽  
Sampling Plans ◽  
Classical Statistics ◽  
Acceptance Sampling Plans ◽  
Neutrosophic Statistics ◽  
Lot Sentencing

The acceptance sampling plans are one of the most important tools for the inspection of a lot of products. Sometimes, it is difficult to study the variable of interest, and some additional or auxiliary information which is correlated to that variable is available. The existing sampling plans having auxiliary information are applied when the full, precise, determinate and clear data is available for lot sentencing. Neutrosophic statistics, which is the extension of classical statistics, can be applied when information about the quality of interest or auxiliary information is unclear and indeterminate. In this paper, we will introduce a neutrosophic regression estimator. We will design a new sampling plan using the neutrosophic regression estimator. The neutrosophic parameters of the proposed plan will be determined through the neutrosophic optimization solution. The efficiency of the proposed plan is discussed. The results of the proposed plan will be explained using real industrial data. From the comparison, it is concluded that the proposed sampling plan is more effective and adequate for the inspection of a lot than the existing plan, under the conditions of uncertainty.

scholarly journals Design of SkSP-R Variables Sampling Plans

2015 ◽  
Vol 38 (2) ◽  
pp. 413-429 ◽  
Author(s):  
Muhammad Aslam ◽  
Saminathan Balamurali ◽  
Chi-Hyuck Jun ◽  
Batool Hussain
Keyword(s):  
Nonlinear Optimization ◽  
Optimization Problem ◽  
Sampling Plan ◽  
Producer’S Risk ◽  
Sample Number ◽  
Sampling Plans ◽  
Average Sample Number ◽  
Nonlinear Optimization Problem ◽  
Better Than ◽  
Average Sample

In this paper, we present the designing of the skip-lot sampling plan including the re-inspection  called SkSP-R. The plan parameters of the proposed plan are determined through a  nonlinear optimization problem by minimizing the average sample number satisfying both the producer's risk and the consumer's risks. The proposed plan is shown to perform better than the existing sampling plans in terms of the average sample number. The application of the proposed plan is explained with the help of illustrative examples.

scholarly journals The W/S Test for Data Having Neutrosophic Numbers: An Application to USA Village Population

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-8 ◽  
Author(s):  
Mohammed Albassam ◽  
Nasrullah Khan ◽  
Muhammad Aslam
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Distributions ◽  
Interval Method ◽  
Power Of Test ◽  
Classical Statistics ◽  
Neutrosophic Statistics ◽  
Village Population

The W/S test under neutrosophic statistics is proposed in this paper. The Monte Carlo simulation under the neutrosophic statistical interval method is proposed and applied to study the sensitivity of various neutrosophic statistical distributions. The power of test curves for neutrosophic distributions is presented. The efficiency of the proposed W/S test under neutrosophic statistics is compared with that of the W/S test under classical statistics. The proposed test is explained with the aid of an example.

Research on the Application of Operation Characteristic Curve in the Sampling Inspection for Foods in Prepackages with Fixed Content

2012 ◽  
Vol 605-607 ◽  
pp. 532-537 ◽  
Author(s):  
Long Xian Zhu ◽  
Pin Lu ◽  
Jing Hong Wang ◽  
Zhong Yin ◽  
Jian Xin He
Keyword(s):  
Characteristic Curve ◽  
Sampling Plan ◽  
Inspection Time ◽  
Practical Application ◽  
Discrimination Power ◽  
Sampling Plans ◽  
Sampling Inspection ◽  
Variable Sampling ◽  
Operation Characteristic ◽  
Metrological Testing

New enterprises for products in prepackages with fixed content always use sampling inspection to make sure the accuracy of the net quantity of their products according to JJF 1070-2005 “Rules of Metrological Testing for Net Quantity of Products in Prepackages with Fixed Content”, but this sampling inspection plan is expensive. The theoretical basis of the variable sampling plan in JJF 1070 was analyzed first. Then based on ISO 3951-1, the variable acceptance standard, a new sampling plan for products in prepackages with fixed content was developed, and it’s operation characteristic curve was drawn. Taking one company in Jinhua city of Zhejiang province of China as an example, a comparative analysis for the practical application of these two sampling plans was carried out. Under the premise that the sampling plan’s discrimination power was unchanged, the results showed that the acceptance effects of two sampling plans waere almost the same, while the reduction of sample size for the new one was 44%, the inspection time and cost were all reduced.

Comment on “Exact Bayesian variable sampling plans for the exponential distribution based on type-I hybrid censored samples” and “its corrections”

2013 ◽  
Vol 44 (2) ◽  
pp. 113-122
Author(s):  
Tachen Liang
Keyword(s):  
Exponential Distribution ◽  
Sampling Plan ◽  
Design Parameters ◽  
Type I ◽  
Sampling Plans ◽  
Bayesian Sampling ◽  
Censored Samples ◽  
Variable Sampling

We compare the performances of two sampling plans, namely, the Lin-Liang-Huang (2002)'s Bayesian sampling plan $(n^*,\xi^*)$ and the Lin-Huang-Balakrishnan (2008a, 2010a)'s exact Bayesian sampling plan $(n_0,r_0,t_0,\xi_0)$. We also comment the accuracy of the values of the design parameters $(n_0,r_0,t_0,\xi_0)$ provided in Lin-Huang-Balakrishnan (2010a). We conclude that among the class of sampling plans $(n,r,t,\xi)$ of Lin et al.~(2008a, 2010a), the exact Bayesian sampling plan does not exist.

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